Photovoltaic power generation equipment operation inspection monitoring method and system based on AIoT

Abstract

The invention relates to the technical field of photovoltaic power generation equipment monitoring, and discloses an AIoT-based photovoltaic power generation equipment operation routing inspection monitoring method and system, and the method comprises the steps: carrying out the routing inspection of the photovoltaic power generation equipment at regular intervals, collecting the sensor data and image data in real time during the operation of the equipment, and carrying out the routing inspection of the photovoltaic power generation equipment; the method comprises the following steps: collecting data of a photovoltaic power generation device, performing denoising and enhancement processing on the collected data, converting data of different types and different ranges into a unified format and range, and then performing feature extraction on the processed data to obtain an electrical state and a physical state of the photovoltaic power generation device and a deformation state of a photovoltaic panel; and then the operation state of the photovoltaic power generation equipment is evaluated based on the obtained state information, the next inspection period is adjusted according to an evaluation result, equipment faults are found in time, fault prediction is carried out, and the operation reliability and the power generation efficiency of the photovoltaic power generation equipment are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation equipment monitoring, and in particular to an AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system. Background Art

[0002] As the global demand for clean energy continues to increase, photovoltaic power generation has been widely used as an important form of renewable energy generation. However, photovoltaic power generation equipment is susceptible to various factors during operation and is prone to failure, which in turn affects power generation efficiency and the normal operation of the equipment.

[0003] At present, the inspection and monitoring of photovoltaic power generation equipment have the following problems: 1. The data processing capacity is limited, and it is impossible to accurately analyze the operating status of complex equipment and predict faults. In addition, the sensors are relatively independent and lack an effective collaborative working mechanism, which cannot fully exert the overall effectiveness of the monitoring system; 2. The inspection cycle cannot be appropriately adjusted according to the current operating status of the equipment, resulting in low inspection efficiency. Therefore, a more efficient and intelligent inspection and monitoring method for the operation of photovoltaic power generation equipment is urgently needed to improve the operating reliability and power generation efficiency of photovoltaic power generation equipment. Summary of the Invention

[0004] The purpose of the present invention is to provide an AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system to solve the above-mentioned technical problems.

[0005] A method for inspecting and monitoring the operation of photovoltaic power generation equipment based on AIoT, the method comprising the following steps: Step S1: perform an inspection on the photovoltaic power generation equipment at regular intervals, and collect the operating parameters of the photovoltaic power generation equipment in real time during the inspection; Step S2: After receiving the collected data, the edge computing device preprocesses the data, including filtering the sensor data; denoising and enhancing the image data; and normalizing the data to convert data of different types and ranges into a unified format and range. Step S3: performing feature extraction on the pre-processed data to extract key features that can reflect the operating status of the equipment; Step S4: Evaluate the operating status of the equipment based on the key features extracted in step S3, and adjust the inspection cycle based on the evaluation results.

[0006] As a further description of the solution of the present invention, the operating parameters of the photovoltaic power generation equipment in step S1 include: electrical parameters, physical state parameters and photovoltaic panel deformation state parameters; The electrical parameters include DC side parameters and AC side parameters, the physical state parameters include thermodynamic parameters and mechanical parameters, and the photovoltaic panel deformation state parameters include microcrack parameters and deformation parameters.

[0007] As a further description of the solution of the present invention, the working process of step S3 includes: Obtain the DC side parameters of the photovoltaic power generation equipment at the current moment, including: photovoltaic panel DC output voltage, photovoltaic panel DC output current and photovoltaic panel DC output power; Obtain the AC side parameters of the photovoltaic power generation equipment at the current moment, including: photovoltaic panel AC output voltage, photovoltaic panel AC output current and photovoltaic panel AC output power; Calculate the DC side state coefficient and AC side state coefficient of the photovoltaic power generation equipment at the current moment according to the obtained parameters; Construct a mathematical model of the electrical state coefficient of photovoltaic power generation equipment, the expression is: ; Where, is the DC side state coefficient, is the AC side state coefficient, is the light intensity, A is the photovoltaic panel area, Ambient temperature, The temperature reference value set for the system, is the temperature correction coefficient, and are the weight coefficients of the DC side and the AC side respectively, is the electrical state coefficient of photovoltaic power generation equipment.

[0008] As a further description of the solution of the present invention, the working process of step S3 further includes: Obtain the thermodynamic parameters of the photovoltaic power generation equipment within the current set time period, including: backplane temperature gradient and junction box temperature rise rate; Obtain the mechanical parameters of the photovoltaic power generation equipment at the current moment, including: bracket inclination deviation and component deformation displacement; Calculate the thermodynamic state coefficient and mechanical state coefficient of the photovoltaic power generation equipment at the current moment according to the obtained parameters; Construct a mathematical model of the physical state coefficient of photovoltaic equipment, the expression is: ; Where, is the thermodynamic state coefficient, is the mechanical state coefficient, The light intensity reference value set for the system, The reference value of photovoltaic panel area set for the system, and are the thermodynamic and mechanical weight coefficients, and are the thermodynamic and mechanical correction factors, is the physical state coefficient of the photovoltaic equipment.

[0009] As a further description of the solution of the present invention, the working process of step S3 further includes: Acquire real-time image data of photovoltaic power generation equipment and extract feature information from the image data, including: the number of microcracks per unit area and the average curvature radius of the photovoltaic panel; Construct a mathematical model of the deformation state coefficient of photovoltaic panels of photovoltaic equipment, and the expression is: ; Where, is the average curvature radius of the photovoltaic panel, is the number of microcracks per unit area of ​​the photovoltaic panel, is the average microcrack length, 、 and are the weight coefficients corresponding to the curvature radius, the number of microcracks and the length of microcracks, is the deformation state coefficient of the photovoltaic panel of the photovoltaic equipment.

[0010] As a further description of the solution of the present invention, the working process of step S4 includes: Based on the key features of the equipment operating status extracted in step S3, the operating status coefficient of the photovoltaic power generation equipment is constructed, and the expression is: ; Where, 、 Represent the weight coefficients of electrical state, physical state and deformation state respectively, is the operating status coefficient of photovoltaic power generation equipment; The operating status of the equipment is evaluated based on the electrical status, physical status and deformation status coefficient of the photovoltaic equipment and the operating status coefficient of the photovoltaic power generation equipment.

[0011] As a further description of the solution of the present invention, the working process of evaluating the operating status of the device includes: Compare the electrical state, physical state and deformation state coefficient of the photovoltaic device with the corresponding state coefficient thresholds set by the system. If any state coefficient is greater than or equal to the state coefficient threshold set by the system, it means that the photovoltaic device is unqualified in this state; otherwise, it means that the photovoltaic device is qualified in this state. If the electrical state, physical state and deformation state are all qualified, the photovoltaic equipment will compare the photovoltaic power generation equipment operating state coefficient with the photovoltaic power generation equipment operating state coefficient threshold set by the system. When the photovoltaic power generation equipment operating state coefficient is greater than or equal to the threshold set by the system, it means that there is a risk in the overall operating state of the photovoltaic equipment, and the inspection cycle is shortened. When the photovoltaic power generation equipment operating state coefficient is less than the threshold set by the system, it means that there is no risk in the overall operating state of the photovoltaic equipment, and the inspection cycle is increased.

[0012] An AIoT-based photovoltaic power generation equipment operation inspection and monitoring system, the system comprising: a data acquisition module, a data processing module, a data analysis module, and a status assessment module; The data acquisition module is used to collect status parameters of photovoltaic power generation equipment; The data processing module is used to filter the sensor data, perform denoising and enhancement processing on the image data, and perform normalization processing on the data; The data analysis module is used to extract features from the pre-processed data to extract key features that can reflect the operating status of the equipment; The status evaluation module is used to evaluate the operating status of the equipment and adjust the inspection cycle according to the evaluation results.

[0013] Beneficial effects of the present invention: 1. Intelligent analysis and evaluation: Integrating artificial intelligence and Internet of Things technologies to extract features, fuse and analyze collected data, it can accurately judge the operating status of equipment, achieve rapid assessment and prediction of faults, and improve the accuracy and timeliness of fault diagnosis.

[0014] 2. Real-time and comprehensive monitoring: The inspection cycle is adjusted in time according to the operating status of the equipment, realizing real-time and comprehensive collection of the operating parameters and appearance status of photovoltaic power generation equipment, and being able to obtain the operating information of the equipment in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below with reference to the accompanying drawings.

[0016] Figure 1 It is a partial flow chart of the AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system provided by the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, the present invention is a method for inspecting and monitoring the operation of photovoltaic power generation equipment based on AIoT, and the method includes the following steps: Step S1: perform an inspection on the photovoltaic power generation equipment at regular intervals, and collect the operating parameters of the photovoltaic power generation equipment in real time during the inspection; Step S2: After receiving the collected data, the edge computing device preprocesses the data, including filtering the sensor data to remove noise interference; denoising and enhancing the image data to improve image quality; and normalizing the data to convert data of different types and ranges into a unified format and range for subsequent analysis. Step S3: performing feature extraction on the pre-processed data to extract key features that can reflect the operating status of the equipment; Step S4: Evaluate the operating status of the equipment based on the key features extracted in step S3, and adjust the inspection cycle based on the evaluation results.

[0019] Through the above technical solution, the present invention conducts an inspection of photovoltaic power generation equipment at regular intervals in order to timely discover equipment failures and predict failures, thereby improving the operating reliability and power generation efficiency of photovoltaic power generation equipment. Sensor data and image data of the equipment during operation are collected in real time, and the collected data are denoised and enhanced. At the same time, data of different types and ranges are converted into a unified format and range, and then feature extraction is performed on the processed data to obtain the electrical state, physical state and deformation state of the photovoltaic power generation equipment and the photovoltaic panel. Then, the operating state of the photovoltaic power generation equipment is evaluated based on the acquired state information, and the next inspection cycle is adjusted according to the evaluation results.

[0020] The operating parameters of the photovoltaic power generation equipment in step S1 include: electrical parameters, physical state parameters and photovoltaic panel deformation state parameters; The electrical parameters include DC side parameters and AC side parameters, the physical state parameters include thermodynamic parameters and mechanical parameters, and the photovoltaic panel deformation state parameters include microcrack parameters and deformation parameters.

[0021] The working process of step S3 includes: Obtain the DC side parameters of the photovoltaic power generation equipment at the current moment, including: photovoltaic panel DC output voltage, photovoltaic panel DC output current and photovoltaic panel DC output power; Obtain the AC side parameters of the photovoltaic power generation equipment at the current moment, including: photovoltaic panel AC output voltage, photovoltaic panel AC output current and photovoltaic panel AC output power; Calculate the DC side state coefficient and AC side state coefficient of the photovoltaic power generation equipment at the current moment according to the obtained parameters; Substitute the PV panel DC output voltage, PV panel DC output current and PV panel DC output power into the following formula to calculate the DC side state coefficient: ; Substitute the PV panel AC output voltage, PV panel AC output current and PV panel AC output power into the following formula to calculate the AC side state coefficient: ; Where, 、 and They are the DC output voltage, DC output current and DC output power of the photovoltaic panel respectively. 、 and They are the reference values ​​of the photovoltaic panel DC output voltage, photovoltaic panel DC output current and photovoltaic panel DC output power set in the system. 、 and They are the AC output voltage, AC output current and AC output power of the photovoltaic panel respectively. 、 and They are the reference values ​​of the photovoltaic panel AC output voltage, photovoltaic panel AC output current and photovoltaic panel AC output power set for the system. 、 and are the DC side weight coefficients, 、 and are the AC side weight coefficients respectively; Construct a mathematical model of the electrical state coefficient of photovoltaic power generation equipment, the expression is: ; Where, is the DC side state coefficient, is the AC side state coefficient, is the light intensity, A is the photovoltaic panel area, Ambient temperature, The temperature reference value set for the system, is the temperature correction coefficient, and are the weight coefficients of the DC side and the AC side respectively, is the electrical state coefficient of photovoltaic power generation equipment.

[0022] Through the above technical solution, this embodiment extracts the characteristics of the current electrical state of the photovoltaic device, obtains the DC side parameters and AC side parameters of the current photovoltaic device respectively, and then calculates the DC side and AC side state coefficients based on the DC side parameters and AC side parameters, and then substitutes them into the mathematical model The electrical state coefficient of photovoltaic power generation equipment is calculated, where: Used to correct non-standard temperatures and simulate the impact of actual working conditions. It is the electrical state per unit light and per unit area, reflecting the energy conversion efficiency of the entire system. It is the weighted average of the DC side state coefficient and the AC side state coefficient, which truly reflects the actual contribution of each parameter.

[0023] The working process of step S3 also includes: Obtain the thermodynamic parameters of the photovoltaic power generation equipment within the current set time period, including: backplane temperature gradient and junction box temperature rise rate; Obtain the mechanical parameters of the photovoltaic power generation equipment at the current moment, including: bracket inclination deviation and component deformation displacement; Calculate the thermodynamic state coefficient and mechanical state coefficient of the photovoltaic power generation equipment at the current moment according to the obtained parameters; The bracket inclination deviation and component deformation displacement are divided by the reference value set by the system, and then the comparison values ​​are weighted and summed to obtain the thermodynamic state coefficient of the photovoltaic power generation equipment. The bracket inclination deviation and component deformation displacement are divided by the reference value set by the system, and then the comparison values ​​are weighted and summed to obtain the mechanical state coefficient of the photovoltaic power generation equipment.

[0024] Construct a mathematical model of the physical state coefficient of photovoltaic equipment, the expression is: ; Where, is the thermodynamic state coefficient, is the mechanical state coefficient, The light intensity reference value set for the system, The reference value of photovoltaic panel area set for the system, and are the thermodynamic and mechanical weight coefficients, and are the thermodynamic and mechanical correction factors, is the physical state coefficient of the photovoltaic equipment.

[0025] Through the above technical solution, this embodiment extracts the characteristics of the current physical state of the photovoltaic device, obtains the thermodynamic parameters and mechanical parameters of the current photovoltaic device, and then calculates the thermodynamic and mechanical state coefficients based on the thermodynamic parameters and mechanical parameters, and then substitutes them into the mathematical model The physical state coefficient of photovoltaic power generation equipment is calculated, where: The light intensity correction term is used to adjust TSC according to actual lighting conditions. When the light intensity is close to the optimal value, the ratio is close to 1. If the light is too strong or insufficient, the effectiveness of TSC will be reduced. The area correction term is used to adjust the PSC according to the actual PV panel area. It reflects the adverse effects that may be caused by too large or too small panel area (such as heat dissipation problems or low cost efficiency).

[0026] The working process of step S3 also includes: Acquire real-time image data of photovoltaic power generation equipment and extract feature information from the image data, including: the number of microcracks per unit area and the average curvature radius of the photovoltaic panel; Construct a mathematical model of the deformation state coefficient of photovoltaic panels of photovoltaic equipment, and the expression is: ; Where, is the average curvature radius of the photovoltaic panel, is the number of microcracks per unit area of ​​the photovoltaic panel, is the average microcrack length, 、 and are the weight coefficients corresponding to the curvature radius, the number of microcracks and the length of microcracks, is the deformation state coefficient of the photovoltaic panel of the photovoltaic equipment.

[0027] Through the above technical solution, this embodiment extracts the features of the current photovoltaic panel deformation state of the photovoltaic equipment, obtains the number of microcracks per unit area and the average curvature radius of the photovoltaic panel through the current photovoltaic panel image data, and obtains the average microcrack length, and then substitutes it into the mathematical model , where It is used instead of the radius of curvature itself, because a smaller radius of curvature means a greater degree of curvature. Therefore, using its reciprocal can intuitively reflect the impact of the degree of curvature on the deformation coefficient. The entire expression is divided by the photovoltaic panel area A to ensure that the deformation coefficient is comparable and not directly affected by the panel size.

[0028] The working process of step S4 includes: Based on the key features of the equipment operating status extracted in step S3, the operating status coefficient of the photovoltaic power generation equipment is constructed, and the expression is: ; Where, 、 Represent the weight coefficients of electrical state, physical state and deformation state respectively, is the operating status coefficient of photovoltaic power generation equipment; The operating status of the equipment is evaluated based on the electrical status, physical status and deformation status coefficient of the photovoltaic equipment and the operating status coefficient of the photovoltaic power generation equipment.

[0029] The working process of evaluating the operating status of the equipment includes: Compare the electrical state, physical state and deformation state coefficient of the photovoltaic device with the corresponding state coefficient thresholds set by the system. If any state coefficient is greater than or equal to the state coefficient threshold set by the system, it means that the photovoltaic device is unqualified in this state; otherwise, it means that the photovoltaic device is qualified in this state. If the electrical state, physical state and deformation state are all qualified, the photovoltaic equipment will compare the photovoltaic power generation equipment operating state coefficient with the photovoltaic power generation equipment operating state coefficient threshold set by the system. When the photovoltaic power generation equipment operating state coefficient is greater than or equal to the threshold set by the system, it means that there is a risk in the overall operating state of the photovoltaic equipment, and the inspection cycle is shortened. When the photovoltaic power generation equipment operating state coefficient is less than the threshold set by the system, it means that there is no risk in the overall operating state of the photovoltaic equipment, and the inspection cycle is increased.

[0030] Through the above technical solution, this embodiment evaluates the operating status of the photovoltaic equipment, compares the electrical state, physical state and deformation state coefficient of the photovoltaic equipment with the corresponding state coefficient threshold value set by the system, and if any state coefficient is greater than or equal to the state coefficient threshold value set by the system, it means that the photovoltaic equipment is unqualified in this state, otherwise it means that the photovoltaic equipment is qualified in this state, and then based on The photovoltaic power generation equipment operating status coefficient is calculated and compared with the photovoltaic power generation equipment operating status coefficient threshold set by the system. When the photovoltaic power generation equipment operating status coefficient is greater than or equal to the threshold set by the system, it indicates that there is a risk in the overall operating status of the photovoltaic equipment, and the inspection cycle is shortened. When the photovoltaic power generation equipment operating status coefficient is less than the threshold set by the system, it indicates that there is no risk in the overall operating status of the photovoltaic equipment, and the inspection cycle is increased.

[0031] An AIoT-based photovoltaic power generation equipment operation inspection and monitoring system, the system comprising: a data acquisition module, a data processing module, a data analysis module, and a status assessment module; The data acquisition module is used to collect status parameters of photovoltaic power generation equipment; The data processing module is used to filter the sensor data, perform denoising and enhancement processing on the image data, and perform normalization processing on the data; The data analysis module is used to extract features from the pre-processed data to extract key features that can reflect the operating status of the equipment; The status evaluation module is used to evaluate the operating status of the equipment and adjust the inspection cycle according to the evaluation results.

[0032] It should be noted that all weight coefficients and correction coefficients in the present invention are empirical values. The coefficients can be adjusted in combination with the characteristics of the type of data to be evaluated. The thresholds set in the present invention are all empirical values.

[0033] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for inspecting and monitoring the operation of photovoltaic power generation equipment based on AIoT, characterized in that: The method comprises the following steps: Step S1: perform an inspection on the photovoltaic power generation equipment at regular intervals, and collect the operating parameters of the photovoltaic power generation equipment in real time during the inspection; Step S2: After receiving the collected data, the edge computing device preprocesses the data, including filtering the sensor data, denoising and enhancing the image data, and normalizing the data to convert data of different types and ranges into a unified format and range. Step S3: performing feature extraction on the pre-processed data to extract key features that can reflect the operating status of the equipment; Step S4: Evaluate the operating status of the equipment based on the key features extracted in step S3, and adjust the inspection cycle based on the evaluation results.

2. The AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system according to claim 1 is characterized in that: The operating parameters of the photovoltaic power generation equipment in step S1 include: electrical parameters, physical state parameters and photovoltaic panel deformation state parameters; The electrical parameters include DC side parameters and AC side parameters, the physical state parameters include thermodynamic parameters and mechanical parameters, and the photovoltaic panel deformation state parameters include microcrack parameters and deformation parameters.

3. The AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system according to claim 2 is characterized in that: The working process of step S3 includes: Obtain the DC side parameters of the photovoltaic power generation equipment at the current moment, including: photovoltaic panel DC output voltage, photovoltaic panel DC output current and photovoltaic panel DC output power; Obtain the AC side parameters of the photovoltaic power generation equipment at the current moment, including: photovoltaic panel AC output voltage, photovoltaic panel AC output current and photovoltaic panel AC output power; Calculate the DC side state coefficient and AC side state coefficient of the photovoltaic power generation equipment at the current moment according to the obtained parameters; Construct a mathematical model of the electrical state coefficient of photovoltaic power generation equipment, the expression is: ； Where, is the DC side state coefficient, is the AC side state coefficient, is the light intensity, A is the photovoltaic panel area, Ambient temperature, The temperature reference value set for the system, is the temperature correction coefficient, and are the weight coefficients of the DC side and the AC side respectively, is the electrical state coefficient of photovoltaic power generation equipment.

4. The AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system according to claim 2 is characterized in that: The working process of step S3 also includes: Obtain the thermodynamic parameters of the photovoltaic power generation equipment within the current set time period, including: backplane temperature gradient and junction box temperature rise rate; Obtain the mechanical parameters of the photovoltaic power generation equipment at the current moment, including: bracket inclination deviation and component deformation displacement; Calculate the thermodynamic state coefficient and mechanical state coefficient of the photovoltaic power generation equipment at the current moment according to the obtained parameters; Construct a mathematical model of the physical state coefficient of photovoltaic equipment, the expression is: ; Where, is the thermodynamic state coefficient, is the mechanical state coefficient, The light intensity reference value set for the system, The reference value of photovoltaic panel area set for the system, and are the thermodynamic and mechanical weight coefficients, and are the thermodynamic and mechanical correction factors, is the physical state coefficient of the photovoltaic equipment.

5. The AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system according to claim 2, characterized in that: The working process of step S3 also includes: Acquire real-time image data of photovoltaic power generation equipment and extract feature information from the image data, including: the number of microcracks per unit area and the average curvature radius of the photovoltaic panel; Construct a mathematical model of the deformation state coefficient of photovoltaic panels of photovoltaic equipment, and the expression is: ； Where, is the average curvature radius of the photovoltaic panel, is the number of microcracks per unit area of ​​the photovoltaic panel, is the average microcrack length, 、 and are the weight coefficients corresponding to the curvature radius, the number of microcracks and the length of microcracks, is the deformation state coefficient of the photovoltaic panel of the photovoltaic equipment.

6. The AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system according to claim 1, characterized in that: The working process of step S4 includes: Based on the key features of the equipment operating status extracted in step S3, the operating status coefficient of the photovoltaic power generation equipment is constructed, and the expression is: ； Where, 、 Represent the weight coefficients of electrical state, physical state and deformation state respectively, is the operating status coefficient of photovoltaic power generation equipment; The operating status of the equipment is evaluated based on the electrical status, physical status and deformation status coefficient of the photovoltaic equipment and the operating status coefficient of the photovoltaic power generation equipment.

7. The AIoT-based photovoltaic power generation equipment operation inspection and monitoring method and system according to claim 6, characterized in that: The working process of evaluating the operating status of the equipment includes: Compare the electrical state, physical state and deformation state coefficient of the photovoltaic device with the corresponding state coefficient thresholds set by the system. If any state coefficient is greater than or equal to the state coefficient threshold set by the system, it means that the photovoltaic device is unqualified in this state; otherwise, it means that the photovoltaic device is qualified in this state. If the electrical state, physical state and deformation state are all qualified, the photovoltaic equipment will compare the photovoltaic power generation equipment operating state coefficient with the photovoltaic power generation equipment operating state coefficient threshold set by the system. When the photovoltaic power generation equipment operating state coefficient is greater than or equal to the threshold set by the system, it means that there is a risk in the overall operating state of the photovoltaic equipment, and the inspection cycle is shortened. When the photovoltaic power generation equipment operating state coefficient is less than the threshold set by the system, it means that there is no risk in the overall operating state of the photovoltaic equipment, and the inspection cycle is increased.

8. A photovoltaic power generation equipment operation inspection and monitoring system based on AIoT, the system being used to execute the photovoltaic power generation equipment operation inspection and monitoring method based on AIoT according to any one of claims 1 to 7, characterized in that: The system includes: a data acquisition module, a data processing module, a data analysis module and a status assessment module; The data acquisition module is used to collect status parameters of photovoltaic power generation equipment; The data processing module is used to filter the sensor data, perform denoising and enhancement processing on the image data, and perform normalization processing on the data; The data analysis module is used to extract features from the pre-processed data to extract key features that can reflect the operating status of the equipment; The status evaluation module is used to evaluate the operating status of the equipment and adjust the inspection cycle according to the evaluation results.

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